Computer vision is an area of science and technology related to artificial systems that obtain information from captured images. The image data can take many forms including, but certainly not limited to, a video sequence or views from one or more cameras.
The general category of computer vision comprises a variety of different subfields. Object recognition is a subfield of computer vision that involves recognizing objects from image data, for example, determining which of a plurality of images includes an object most similar to an object included in a target image. Another subfield is scene recognition, which involves recognizing a scene from image data, for example, determining which of a plurality of images includes a scene most similar to an object included in a target image. Computer vision is often utilized as a basis for automating a variety of practical applications including, but certainly not limited to, autonomous robot navigation and unsupervised security functions. For example, robot and security systems can be configured to initiate a particular response when a particular object or scene is automatically detected and identified.
Currently, there are systems that support a broad range of recognition-oriented computer vision tasks including automated scene and object recognition. While some of these systems may perform recognition tasks with a reasonable degree of accuracy, performance is not always an efficient endeavor, especially in terms of the required computer processing and/or memory resources. Further, many existing systems are not effective in terms of providing invariant image recognition.
The discussion above is merely provided for general background information and is not intended for use as an aid in determining the scope of the claimed subject matter.